{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/137833"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/137833","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Radiomic and Image-Based Biomechanical Approaches for Sonographic Evaluation of the Thoracolumbar Fascia in Patients With Mechanical Low Back Pain","abstract":"Low back pain (LBP) is the most common musculoskeletal ailment worldwide and a leading cause of disability. It remains highly challenging to treat clinically due to its complex, multifactorial nature. A growing body of literature provides evidence that the thoracolumbar fascia (TLF)—a densely woven network of collagen fibers that supports and stabilizes the back and trunk—contributes to LBP. Yet substantial gaps remain in our understanding of the TLF's contribution to LBP and in rigorous methods to investigate the structure and function of this tissue in vivo. Ultrasound (US) imaging holds significant promise for point-of-care clinical assessment of the TLF, however there exists limited evidence that commonly used morphological assessments, such as thickness and echogenicity, can reliably distinguish the TLF of individuals with and without LBP. There is a critical need for reliable US-based methods of evaluating the TLF to aid in diagnosis, treatment, and monitoring of LBP. Radiomics, an emerging technique that uses mathematical algorithms to extract quantitative features from medical images, presents a promising approach to augment conventional US image interpretation methods. Image-based biomechanical techniques to quantify movement and tissue properties from medical images and videos can provide further insight into the tissue characteristics and behavior. The work presented in this dissertation focuses on the development and evaluation of rigorous, sonography-based methods of evaluating the TLF to support diagnosis, treatment and monitoring of TLF-associated LBP. The techniques investigated include automated segmentation to aid in distinguishing the TLF within sonograms, sonogram standardization methods to address variations arising from differing image acquisition conditions, methods of estimating TLF displacement from ultrasound recordings, and the utility of radiomic techniques for automating clinical interpretation of TLF sonograms. Following development and evaluation of these radiomic and image-based biomechanical techniques, they were applied in conjunction with multimodal US imaging to compare TLF characteristics and function in individuals with and without LBP.","abstract_html":"Low back pain (LBP) is the most common musculoskeletal ailment worldwide and a leading cause of disability. It remains highly challenging to treat clinically due to its complex, multifactorial nature. A growing body of literature provides evidence that the thoracolumbar fascia (TLF)—a densely woven network of collagen fibers that supports and stabilizes the back and trunk—contributes to LBP. Yet substantial gaps remain in our understanding of the TLF's contribution to LBP and in rigorous methods to investigate the structure and function of this tissue in vivo. Ultrasound (US) imaging holds significant promise for point-of-care clinical assessment of the TLF, however there exists limited evidence that commonly used morphological assessments, such as thickness and echogenicity, can reliably distinguish the TLF of individuals with and without LBP. There is a critical need for reliable US-based methods of evaluating the TLF to aid in diagnosis, treatment, and monitoring of LBP. Radiomics, an emerging technique that uses mathematical algorithms to extract quantitative features from medical images, presents a promising approach to augment conventional US image interpretation methods. Image-based biomechanical techniques to quantify movement and tissue properties from medical images and videos can provide further insight into the tissue characteristics and behavior. The work presented in this dissertation focuses on the development and evaluation of rigorous, sonography-based methods of evaluating the TLF to support diagnosis, treatment and monitoring of TLF-associated LBP. The techniques investigated include automated segmentation to aid in distinguishing the TLF within sonograms, sonogram standardization methods to address variations arising from differing image acquisition conditions, methods of estimating TLF displacement from ultrasound recordings, and the utility of radiomic techniques for automating clinical interpretation of TLF sonograms. Following development and evaluation of these radiomic and image-based biomechanical techniques, they were applied in conjunction with multimodal US imaging to compare TLF characteristics and function in individuals with and without LBP.","abstract_has_math":false,"creators":["Flynn-Smith, Georgina Bramwell"],"institution":"Virginia Tech","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Biomedical Engineering","degree_department":"Department of Biomedical Engineering and Mechanics","school":null,"contributors":[],"advisors":[],"committee_chairs":["Wang, Vincent M."],"committee_members":["De Vita, Raffaella","Iatridis, James","Kozar, Albert John","Rahbar, Elaheh","Han, Aiguo"],"year":2025,"date_issued":"2025-09-25","date_published":"2025-09-25","updated_at":"2026-07-22T22:19:03Z","subjects":["Radiomics","Biomechanics","Ultrasound Imaging","Thoracolumbar Fascia","Low Back Pain"],"languages":["en"],"rights":["Creative Commons Attribution 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by/4.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44598"],"render_values":[{"text":"vt_gsexam:44598","href":null,"code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10919/137833","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Wang, Vincent M."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["De Vita, Raffaella","Iatridis, James","Kozar, Albert John","Rahbar, Elaheh","Han, Aiguo"]},{"key":"dc:contributor.department","label":"Department","values":["Department of Biomedical Engineering and Mechanics"]},{"key":"dc:creator","label":"Author","values":["Flynn-Smith, Georgina Bramwell"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-09-26T08:00:42Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-09-26T08:00:42Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-09-25"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Radiomics","Biomechanics","Ultrasound Imaging","Thoracolumbar Fascia","Low Back Pain"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Creative Commons Attribution 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:44598"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10919/137833"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Low back pain (LBP) is the most common musculoskeletal ailment worldwide and a leading cause of disability. It remains highly challenging to treat clinically due to its complex, multifactorial nature. A growing body of literature provides evidence that the thoracolumbar fascia (TLF)—a densely woven network of collagen fibers that supports and stabilizes the back and trunk—contributes to LBP. Yet substantial gaps remain in our understanding of the TLF's contribution to LBP and in rigorous methods to investigate the structure and function of this tissue in vivo. Ultrasound (US) imaging holds significant promise for point-of-care clinical assessment of the TLF, however there exists limited evidence that commonly used morphological assessments, such as thickness and echogenicity, can reliably distinguish the TLF of individuals with and without LBP. There is a critical need for reliable US-based methods of evaluating the TLF to aid in diagnosis, treatment, and monitoring of LBP. Radiomics, an emerging technique that uses mathematical algorithms to extract quantitative features from medical images, presents a promising approach to augment conventional US image interpretation methods. Image-based biomechanical techniques to quantify movement and tissue properties from medical images and videos can provide further insight into the tissue characteristics and behavior. The work presented in this dissertation focuses on the development and evaluation of rigorous, sonography-based methods of evaluating the TLF to support diagnosis, treatment and monitoring of TLF-associated LBP. The techniques investigated include automated segmentation to aid in distinguishing the TLF within sonograms, sonogram standardization methods to address variations arising from differing image acquisition conditions, methods of estimating TLF displacement from ultrasound recordings, and the utility of radiomic techniques for automating clinical interpretation of TLF sonograms. Following development and evaluation of these radiomic and image-based biomechanical techniques, they were applied in conjunction with multimodal US imaging to compare TLF characteristics and function in individuals with and without LBP."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Low back pain is one of the most common health problems worldwide and a leading cause of disability. Despite its prevalence, it remains difficult to treat because it can stem from many different causes. Recent research suggests that a connective tissue in the lower back called the thoracolumbar fascia (TLF) may play an important role in low back pain. However, scientists still know very little about how this tissue contributes to pain or how best to study it in living people. Ultrasound imaging is a safe, affordable tool that can be used at the point of care to examine the TLF, but current methods for interpreting these images aren't always reliable. This research explores new ways to analyze ultrasound images of the TLF using advanced computer techniques. These include radiomics, which uses mathematical tools to extract detailed information from medical images, and biomechanical analysis, which helps measure how tissues move and behave. This dissertation presents a set of new methods for evaluating the TLF using ultrasound. These include tools to automatically identify the TLF in images, techniques to standardize images taken under different conditions, ways to measure tissue movement from ultrasound videos, and approaches to help automate clinical interpretation. After developing and testing these tools, they were used to compare the TLF in people with and without low back pain. The goal is to improve how low back pain is diagnosed, treated, and monitored—by making it easier to study this important but overlooked tissue."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Doctor of Philosophy"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Radiomic and Image-Based Biomechanical Approaches for Sonographic Evaluation of the Thoracolumbar Fascia in Patients With Mechanical Low Back Pain"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Wang, Vincent M."],"dc:contributor.committeemember":["De Vita, Raffaella","Iatridis, James","Kozar, Albert John","Rahbar, Elaheh","Han, Aiguo"],"dc:contributor.department":["Department of Biomedical Engineering and Mechanics"],"dc:creator":["Flynn-Smith, Georgina Bramwell"],"dc:date.accessioned":["2025-09-26T08:00:42Z"],"dc:date.available":["2025-09-26T08:00:42Z"],"dc:date.issued":["2025-09-25"],"dc:description.abstract":["Low back pain (LBP) is the most common musculoskeletal ailment worldwide and a leading cause of disability. It remains highly challenging to treat clinically due to its complex, multifactorial nature. A growing body of literature provides evidence that the thoracolumbar fascia (TLF)—a densely woven network of collagen fibers that supports and stabilizes the back and trunk—contributes to LBP. Yet substantial gaps remain in our understanding of the TLF's contribution to LBP and in rigorous methods to investigate the structure and function of this tissue in vivo. Ultrasound (US) imaging holds significant promise for point-of-care clinical assessment of the TLF, however there exists limited evidence that commonly used morphological assessments, such as thickness and echogenicity, can reliably distinguish the TLF of individuals with and without LBP. There is a critical need for reliable US-based methods of evaluating the TLF to aid in diagnosis, treatment, and monitoring of LBP. Radiomics, an emerging technique that uses mathematical algorithms to extract quantitative features from medical images, presents a promising approach to augment conventional US image interpretation methods. Image-based biomechanical techniques to quantify movement and tissue properties from medical images and videos can provide further insight into the tissue characteristics and behavior. The work presented in this dissertation focuses on the development and evaluation of rigorous, sonography-based methods of evaluating the TLF to support diagnosis, treatment and monitoring of TLF-associated LBP. The techniques investigated include automated segmentation to aid in distinguishing the TLF within sonograms, sonogram standardization methods to address variations arising from differing image acquisition conditions, methods of estimating TLF displacement from ultrasound recordings, and the utility of radiomic techniques for automating clinical interpretation of TLF sonograms. Following development and evaluation of these radiomic and image-based biomechanical techniques, they were applied in conjunction with multimodal US imaging to compare TLF characteristics and function in individuals with and without LBP."],"dc:description.abstractgeneral":["Low back pain is one of the most common health problems worldwide and a leading cause of disability. Despite its prevalence, it remains difficult to treat because it can stem from many different causes. Recent research suggests that a connective tissue in the lower back called the thoracolumbar fascia (TLF) may play an important role in low back pain. However, scientists still know very little about how this tissue contributes to pain or how best to study it in living people. Ultrasound imaging is a safe, affordable tool that can be used at the point of care to examine the TLF, but current methods for interpreting these images aren't always reliable. This research explores new ways to analyze ultrasound images of the TLF using advanced computer techniques. These include radiomics, which uses mathematical tools to extract detailed information from medical images, and biomechanical analysis, which helps measure how tissues move and behave. This dissertation presents a set of new methods for evaluating the TLF using ultrasound. These include tools to automatically identify the TLF in images, techniques to standardize images taken under different conditions, ways to measure tissue movement from ultrasound videos, and approaches to help automate clinical interpretation. After developing and testing these tools, they were used to compare the TLF in people with and without low back pain. The goal is to improve how low back pain is diagnosed, treated, and monitored—by making it easier to study this important but overlooked tissue."],"dc:description.degree":["Doctor of Philosophy"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:44598"],"dc:identifier.uri":["https://hdl.handle.net/10919/137833"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["Creative Commons Attribution 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by/4.0/"],"dc:subject":["Radiomics","Biomechanics","Ultrasound Imaging","Thoracolumbar Fascia","Low Back Pain"],"dc:title":["Radiomic and Image-Based Biomechanical Approaches for Sonographic Evaluation of the Thoracolumbar Fascia in Patients With Mechanical Low Back Pain"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Biomedical Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:03Z"}